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END OF TERMS AND CONDITIONS
How to Apply These Terms to Your New Programs
If you develop a new program, and you want it to be of the greatest
possible use to the public, the best way to achieve this is to make it
free software which everyone can redistribute and change under these terms.
To do so, attach the following notices to the program. It is safest
to attach them to the start of each source file to most effectively
convey the exclusion of warranty; and each file should have at least
the "copyright" line and a pointer to where the full notice is found.
<one line to give the program's name and a brief idea of what it does.>
Copyright (C) <year> <name of author>
This program is free software; you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation; either version 2 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License along
with this program; if not, write to the Free Software Foundation, Inc.,
51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
Also add information on how to contact you by electronic and paper mail.
If the program is interactive, make it output a short notice like this
when it starts in an interactive mode:
Gnomovision version 69, Copyright (C) year name of author
Gnomovision comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
This is free software, and you are welcome to redistribute it
under certain conditions; type `show c' for details.
The hypothetical commands `show w' and `show c' should show the appropriate
parts of the General Public License. Of course, the commands you use may
be called something other than `show w' and `show c'; they could even be
mouse-clicks or menu items--whatever suits your program.
You should also get your employer (if you work as a programmer) or your
school, if any, to sign a "copyright disclaimer" for the program, if
necessary. Here is a sample; alter the names:
Yoyodyne, Inc., hereby disclaims all copyright interest in the program
`Gnomovision' (which makes passes at compilers) written by James Hacker.
<signature of Ty Coon>, 1 April 1989
Ty Coon, President of Vice
This General Public License does not permit incorporating your program into
proprietary programs. If your program is a subroutine library, you may
consider it more useful to permit linking proprietary applications with the
library. If this is what you want to do, use the GNU Lesser General
Public License instead of this License.
README.md
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@@ -5,7 +5,7 @@
* :rocket: Serena is a powerful, fully-featured **coding agent that works directly on your codebase**.
* :wrench: Serena **integrates with existing LLMs**, providing them with essential **semantic code retrieval and editing tools!**
* :free: Serena is **free to use**. No additional API keys or subscriptions required!
* :free: Serena is **free to use**. No API keys or subscriptions required!
Q: Can I have a state-of-the-art coding agent without paying (enormous) API costs
or constantly purchasing tokens?
@@ -13,15 +13,29 @@ A: Yes, you can!
By integrating Serena with your favourite (even free) LLM and thereby enabling it
to perform coding tasks directly on your codebase.
### Demonstration
Here is a demonstration of Serena implementing a small feature for itself (a better log GUI) with Claude Desktop.
Note how Serena's tools enable Claude to find and edit the right symbols.
https://github.com/user-attachments/assets/6eaa9aa1-610d-4723-a2d6-bf1e487ba753
### LLM Integration
Serena provides the necessary [tools](#full-list-of-tools) for coding workflows, but an LLM is required to do the actual work,
orchestrating tool use.
Serena can be integrated with an LLM in several ways:
* by using the **model context protocol (MCP)**.
Serena provides an MCP server which integrates with Claude (and [soon also ChatGPT](https://x.com/OpenAIDevs/status/1904957755829481737)).
* by using **Agno – the model-agnostic agent framework**.
* by using **Agno – the model-agnostic agent framework**.
Serena's Agno-based agent allows you to turn virtually any LLM into a coding agent, whether it's provided by Google, OpenAI or DeepSeek (with a paid API key)
or a free model provided by Ollama, Together or Anyscale.
* by incorporating Serena's tools into an agent framework of your choice.
Serena's tool implementation is decoupled from the framework-specific code and can thus easily be adapted to any agent framework.
### Programming Language Support & Semantic Analysis
Serena's semantic code analysis capabilities build on **language servers** using the widely implemented
language server protocol (LSP). The LSP provides a set of versatile code querying
and editing functionalities based on symbolic understanding of the code.
@@ -41,9 +55,14 @@ With Serena, we provide
* Ruby (untested)
* Go (untested)
* C# (untested)
Further languages can easily be supported by providing a shallow adapter for a new language server
These languages are supported by the language server library [multilspy](https://github.com/microsoft/multilspy), which Serena uses under the hood.
But we did not explicitly test whether the support for these languages actually works.
Further languages can, in principle, easily be supported by providing a shallow adapter for a new language server
implementation.
## Table of Contents
<!-- Created with markdown-toc -i README.md -->
<!-- Install it with npm install -g markdown-toc -->
<!-- toc -->
@@ -93,9 +112,9 @@ We thus built Serena with the prospect of being able to cancel most other subscr
## What Can I Use Serena For?
You can use Serena for any coding tasks - analyzing, planning, editing and so on.
You can use Serena for any coding tasks – analyzing, planning, editing and so on.
Serena can read, write and execute code, read logs and the terminal output.
Vibe coding is possible, and if you want to almost feel like "the code no longer exists"
"Vibe coding" is possible, and if you want to almost feel like "the code no longer exists",
you may find Serena even more adequate for vibing than an agent inside an IDE
(since you will have a separate GUI that really lets you forget).
@@ -107,27 +126,35 @@ Vibe coding is possible, and if you want to almost feel like "the code no longer
2. Clone the repository to `/path/to/serena`.
3. Create a configuration file for your project, say `myproject.yml` based on the template in [myproject.demo.yml](myproject.demo.yml).
4. Configure the MCP server in your client.
For Claude Desktop, go to File / Settings / Developer / MCP Servers / Edit Config,
which will let you open the json file `claude_desktop_config.json`. Add the following (with adjusted paths) to enable Serena:
For [Claude Desktop](https://claude.ai/download) (available for Windows and macOS), go to File / Settings / Developer / MCP Servers / Edit Config,
which will let you open the JSON file `claude_desktop_config.json`. Add the following (with adjusted paths) to enable Serena:
```json
{
"mcpServers": {
"serena": {
"command": "/abs/path/to/uv",
"args": ["run", "--directory", "/abs/path/to/serena", "serena-mcp-server", "/abs/path/to/myproject.yml"]
}
}
}
```
```json
{
"mcpServers": {
"serena": {
"command": "/abs/path/to/uv",
"args": ["run", "--directory", "/abs/path/to/serena", "serena-mcp-server", "/abs/path/to/myproject.yml"]
}
}
}
```
When using paths containing backslashes on Windows, be sure to escape them correctly (`\\`).
When using paths containing backslashes on Windows, be sure to escape them correctly (`\\`).
That's it! Save the config and then restart Claude Desktop (be sure to fully quit the application, as closing Claude will just minimize it to the system tray).
You should then see the Serena MCP tools in your chat interface (notice the small hammer icon).
That's it! Save the config and then restart Claude Desktop.
Note that Serena is always configured *for a single project*. To use it for another, you will have to
write a new configuration file and adjust the config in the MCP client.
⚠️ Be sure to fully quit the Claude Desktop application, as closing Claude will just minimize it to the system tray – at least on Windows.
After restarting, you should Serena's tools in your chat interface (notice the small hammer icon).
ℹ️ Note that MCP servers which use stdio as a protocol are somewhat unusual as far as client/server architectures go, as the server
necessarily has to be started by the client in order for communication to take place via the server's standard input/output stream.
In other words, you do not need to start the server yourself. The client application (e.g. Claude Desktop) takes care of this and
therefore needs to be configured with a launch command.
ℹ️ Furthermore note that Serena is always configured *for a single project*. To use it for another, you will have to
write a new configuration file, adjust the configuration to point to it and then restart the client.
For more information on MCP servers with Claude Desktop, see [the official quick start guide](https://modelcontextprotocol.io/quickstart/user).
@@ -136,7 +163,7 @@ For more information on MCP servers with Claude Desktop, see [the official quick
Agno is a model-agnostic agent framework that allows you to use Serena with a large number of underlying LLMs.
While Agno is not yet entirely stable, we chose it, because it comes with its own open-source UI,
making it easy to directly use the agent.
making it easy to directly use the agent using a chat interface.
Here's how it works (see also [Agno's documentation](https://docs.agno.com/introduction/playground)):
@@ -176,16 +203,23 @@ Here's how it works (see also [Agno's documentation](https://docs.agno.com/intro
Connect the UI to the agent you started above and start chatting. You will have
the same tools as in the MCP server version.
IMPORTANT: Contrary to the MCP server approach, tool execution in the Agno UI does
not ask for the user's permission. Note that the shell
tool can perform arbitrary code execution. While we have never encountered any issues with
this in our testing with Claude, this may not be entirely safe.
Here is a short demo of Serena performing a small analysis task with the newest Gemini model:
https://github.com/user-attachments/assets/ccfcb968-277d-4ca9-af7f-b84578858c62
⚠️ IMPORTANT: In contrast to the MCP server approach, tool execution in the Agno UI does
not ask for the user's permission. The shell tool is particularly critical, as it can perform arbitrary code execution.
While we have never encountered any issues with
this in our testing with Claude, allowing this may not be entirely safe.
You may choose to disable certain tools for your setup in your Serena project's
configuration file (`myproject.yml`).
configuration file (`.yml`).
## Serena's Tools and Configuration
Serena combines tools for semantic code retrieval with editing capabilities and shell execution.
Find the complete list of tools [below](#serenas-tools-and-configuration).
The use of all tools is generally recommended, as this allows Serena to provide the most value:
Only by executing shell commands (in particular, tests) can Serena identify and correct mistakes
@@ -210,8 +244,6 @@ without modifying the codebase, you can consider disabling the editing tools in
In general, be sure to back up your work and use a version control system in order to avoid
losing any work.
Find the complete list of tools [here](#serenas-tools-and-configuration).
## Comparison with Other Coding Agents
@@ -219,7 +251,6 @@ To our knowledge, Serena is the first fully-featured coding agent where the
entire functionality
is available through an MCP server, thus not requiring API keys or
subscriptions.
Here a brief comparison with other tools:
### Subscription-Based Coding Agents
@@ -268,8 +299,7 @@ an API key and bypassing the API costs. This is a unique feature of Serena.
### Other MCP-Based Coding Agents
There are other MCP servers meant for coding, like for
example [DesktopCommander](https://github.com/wonderwhy-er/DesktopCommanderMCP) and
There are other MCP servers designed for coding, like [DesktopCommander](https://github.com/wonderwhy-er/DesktopCommanderMCP) and
[codemcp](https://github.com/ezyang/codemcp).
However, to the best of our knowledge, none of them provide semantic code
retrieval and editing tools; they rely purely on text-based analysis.
@@ -277,37 +307,40 @@ It is the integration of language servers and the MCP that makes Serena unique
and so powerful for challenging coding tasks, especially in the context of
larger codebases.
## Limitations of MCP Servers
## Stability Issues in MCP Client-Server Interactions
The support for MCP Servers in Claude Desktop and the various MCP Server SDKs are relatively new technologies,
and we found them to be flaky. Sometimes Claude Desktop will crash on a tool execution (with an asyncio error or
something else of this kind). It can show error messages which have no effect, and on the contrary, fail to
show error messages when things go wrong. The working configuration of an MCP server may vary from platform to
platform and from client to client (we recommend always using absolute paths, as relative paths may be sources of
errors). The language server is running in a separate thread and is called with asyncio - sometimes
Claude Desktop lets it crash.
We expect these stability issues to improve over time.
The support for MCP Servers in Claude Desktop and the various MCP Server SDKs are relatively new developments,
and we found them to be somewhat unstable. Sometimes, Claude Desktop will crash on a tool execution (with an asyncio error or
something else of this kind). On the one hand, it can display show error messages that are no of consequence, and on the other, it can fail to
show error messages when things fail irrecoverably.
Yet we expect these stability issues to improve over time.
For now, you may have to restart Claude Desktop multiple times, may have to manually cleanup python processes,
The working configuration of an MCP server may vary from platform to
platform and from client to client. We recommend always using absolute paths, as relative paths may be sources of
errors. The language server is running in a separate sub-process and is called with asyncio – sometimes
Claude Desktop lets it crash. If you have Serena's log window enabled, and it disappears, you'll know what happened.
For now, you may have to restart Claude Desktop multiple times, may have to manually cleanup lingering processes,
and you may experiences freezes in conversations.
Just try again in the latter case. You can also switch to the API-key based agent mode if you are willing to pay for a potentially
smoother experience (see [section on Agno](#agno)).
Just try again in the latter case.
Feel free to open issues if you encounter setup problems that you cannot solve.
### Serena Logging
To help with troubleshooting, we have written a small GUI utility for logging. We recommend that you enable it
through the `myproject.yml` if you encounter problems. For Claude Desktop, there are also the MCP logs that can help
through the project configuration (`myproject.yml`) if you encounter problems. For Claude Desktop, there are also the MCP logs that can help
identify issues.
## Onboarding and Memories
By default, Serena will perform an onboarding process when
it is started for the first time for a project. It will save some information
as memories to `.serena/memories/` in the project directory.
it is started for the first time for a project.
The goal of the process is for Serena to get familiar with the project
and to store memories, which it can then draw upon in future interactions.
The memories are human-readable and will be used as references for further tasks.
Feel free to read and adjust them as needed, you can also add new ones manually.
Memroies are files stored in `.serena/memories/` in the project directory,
which the agent can choose to read.
Feel free to read and adjust them as needed; you can also add new ones manually.
Every file in the `.serena/memories/` directory is a memory file.
We found the memories to significantly improve the user experience with Serena.
@@ -344,8 +377,8 @@ up the context. We recommend that you switch to another conversation
once the onboarding is performed in order to not run out of tokens. The onboarding will
only be performed once, unless you explicitly trigger it.
After the onboarding we recommend that you have a quick look at the memories and
if desired edit them or add new ones.
After the onboarding, we recommend that you have a quick look at the memories and,
if necessary, edit them or add additional ones.
### Before Editing Code
@@ -354,11 +387,11 @@ this make it easier for you to inspect the changes, but also the model itself wi
have a chance of seeing what it has changed by calling `git diff` and thereby
correct itself or continue working in a followup conversation if needed.
**Important**: since Serena will write to files using the system-native line endings
:warning: **Important**: since Serena will write to files using the system-native line endings
and it might want to look at the git diff, it is important to
set `git config core.autocrlf` to `true` on Windows.
With `git config core.autocrlf` set to `false` on Windows you may end up with huge diffs
only due to line endings. It is generally a good idea to do this on Windows
With `git config core.autocrlf` set to `false` on Windows, you may end up with huge diffs
only due to line endings. It is generally a good idea to enable this git setting on Windows:
```shell
git config --global core.autocrlf true
@@ -366,10 +399,10 @@ git config --global core.autocrlf true
### Potential Issues in Code Editing
In our experience, LLMs are really bad at counting, which means they have problems
inserting blocks of code at the right place. Most editing operations can be performed
on a symbolic level, through which this problem is overcome. However, sometimes
insertions beyond that are useful.
In our experience, LLMs are really bad at counting, i.e. they have problems
inserting blocks of code in the right place. Most editing operations can be performed
on a symbolic level, allowing this problem is overcome. However, sometimes,
line-level insertions are useful.
Serena is instructed to double-check the line numbers and any code blocks that it will
edit, but you may find it useful to explicitly tell it how to edit code if you run into
@@ -378,7 +411,7 @@ problems.
### Running Out of Context
For long and complicated tasks, or tasks where Serena has read a lot of content, you
may come close to the limits of context tokens. In that case it is often a good idea to continue
may come close to the limits of context tokens. In that case, it is often a good idea to continue
in a new conversation. Serena has a dedicated tool to create a summary of the current state
of the progress and all relevant info for continuing it. You can request to create this summary and
write it to a memory. Then, in a new conversation, you can just ask Serena to read the memory and
@@ -410,14 +443,13 @@ typed code - it will not only help you but also help your AI ;).
### Logging, Linting, and Testing
Serena cannot debug (no coding assistant can do that at the moment, to our knowledge). This means
that for improving the results within an "agent-loop", Serena needs to acquire information by
executing tests, running scripts, linting and so on. It is often very helpful to include many log
messages with explicit information and to have good tests. Especially the latter often help the agent
Serena cannot debug (no coding assistant can do this at the moment, to our knowledge). This means
that for improving the results within an _agent loop_, Serena needs to acquire information by
executing tests, running scripts, performing linting and so on. It is often very helpful to include many log
messages with explicit information and to have meaningful tests. Especially the latter often help the agent
to self-correct.
We generally recommend to start an editing task from a state where all linting checks and tests pass, this
way the info extracted from running these commands is of most use to the agent.
We generally recommend to start an editing task from a state where all linting checks and tests pass.
### General Advice
@@ -430,10 +462,9 @@ and then continue with the implementation in another (potentially after creating
## Acknowledgements
We built Serena on top of multiple existing open-source technologies, to which we are very grateful.
Here a short list of the most important ones:
We built Serena on top of multiple existing open-source technologies, the most important ones being:
1. [Multilspy](https://github.com/microsoft/multilspy).
1. [multilspy](https://github.com/microsoft/multilspy).
A beautifully designed wrapper around language servers following the LSP. It
was not easily extendable with the symbolic
logic that Serena required, so instead of incorporating it as dependency, we
@@ -441,12 +472,12 @@ Here a short list of the most important ones:
and adapted it to our needs.
2. [Python MCP SDK](https://github.com/modelcontextprotocol/python-sdk)
3. [Agno](https://github.com/agno-agi/agno) and
agno's [agent-ui](https://github.com/agno-agi/agent-ui),
which we use to allow Serena to work with any model, not just those that
support the MCP.
the associated [agent-ui](https://github.com/agno-agi/agent-ui),
which we use to allow Serena to work with any model, beyond the ones
supporting the MCP.
4. All the language servers that we use through multilspy.
Without these projects, Serena would not have been possible, or would at least much more difficult to build.
Without these projects, Serena would not have been possible (or would have been significantly more difficult to build).
## Customizing Serena
@@ -459,7 +490,6 @@ to seeing what the community will come up with! For details on contributing, see
Here the full list of Serena's default tools with a short description (the output of `uv run serena-list-tools`)
```
* `check_onboarding_performed`: Checks whether the onboarding was already performed.
* `create_text_file`: Creates/overwrites a file in the project directory.
* `delete_lines`: Deletes a range of lines within a file.
@@ -485,4 +515,4 @@ Here the full list of Serena's default tools with a short description (the outpu
* `think_about_task_adherence`: Thinking tool for determining whether the agent is still on track with the current task.
* `think_about_whether_you_are_done`: Thinking tool for determining whether the task is truly completed.
* `write_memory`: Writes a named memory (for future reference) to Serena's project-specific memory store.
```
pyproject.toml
+2 -1
View File
@@ -37,7 +37,7 @@ serena-mcp-server = "serena.mcp:start_mcp_server"
serena-list-tools = "serena.agent:print_tool_overview"
[project.license]
text = "MIT"
text = "GPL-2.0"
[project.optional-dependencies]
dev = [
@@ -55,6 +55,7 @@ dev = [
agno = [
"agno>=1.2.6",
"fastapi>=0.115.12",
"sqlalchemy>=2.0.40",
]
anthropic = [
"anthropic>=0.49.0",
scripts/agno_agent.py
+50 -43
View File
@@ -1,7 +1,8 @@
import argparse
import os
from logging import Logger
from pathlib import Path
import click
from agno.agent.agent import Agent
from agno.memory.agent import AgentMemory
from agno.models.anthropic.claude import Claude
@@ -10,7 +11,6 @@ from agno.playground.playground import Playground
from agno.playground.serve import serve_playground_app
from agno.storage.sqlite import SqliteStorage
from dotenv import load_dotenv
from fastapi import FastAPI
from sensai.util import logging
from sensai.util.helper import mark_used
@@ -19,57 +19,64 @@ from serena.agno import SerenaAgnoToolkit
mark_used(Gemini, Claude)
os.chdir(os.path.dirname(os.path.abspath(__file__)))
os.chdir(Path(__file__).parent)
Logger.root.setLevel(logging.INFO)
load_dotenv()
# The app object must be in the module scope so that the server can access it for hot reloading
app: FastAPI | None = None
parser = argparse.ArgumentParser(description="Serena coding assistant")
parser.add_argument("--project-file", required=True, help="Path to the project file, either absolute or relative to the root directory")
args = parser.parse_args()
project_file = Path(args.project_file).resolve()
# If project file path is relative, make it absolute by joining with project root
if not project_file.is_absolute():
# Get the project root directory (parent of scripts directory)
project_root = Path(__file__).parent.parent
project_file = project_root / args.project_file
# Ensure the path is normalized and absolute
project_file = project_file.resolve()
@click.command()
@click.option("--project-file", default="../myproject.yml", help="Path to the project configuration YAML file")
def main(project_file):
global app # noqa: PLW0603
serena_agent = SerenaAgent(project_file, start_language_server=True)
serena_agent = SerenaAgent(str(project_file), start_language_server=True)
# Even though we don't want to keep history between sessions,
# for the agno ui to work as a conversation, we a persistent storage on disk
# This storage should be deleted between sessions.
# Note that this might collide with custom options for the agent, like adding vector-search based tools.
# See here for an explanation: https://www.reddit.com/r/agno/comments/1jk6qea/regarding_the_built_in_memory/
sql_db_path = os.path.join("tmp", "agent_storage.db")
os.makedirs(os.path.dirname(sql_db_path), exist_ok=True)
# delete the db file if it exists
if os.path.exists(sql_db_path):
os.remove(sql_db_path)
# Even though we don't want to keep history between sessions,
# for the agno ui to work as a conversation, we a persistent storage on disk
# This storage should be deleted between sessions.
# Note that this might collide with custom options for the agent, like adding vector-search based tools.
# See here for an explanation: https://www.reddit.com/r/agno/comments/1jk6qea/regarding_the_built_in_memory/
sql_db_path = Path("tmp") / "agent_storage.db"
sql_db_path.parent.mkdir(exist_ok=True)
# delete the db file if it exists
if sql_db_path.exists():
sql_db_path.unlink()
model = Claude(id="claude-3-7-sonnet-20250219")
# Or use any other model supported by agno, e.g. the newest Gemini:
# model = Gemini(id="gemini-2.5-pro-exp-03-25")
# model = Claude(id="claude-3-7-sonnet-20250219")
# Or use any other model supported by agno, e.g. the newest Gemini:
model = Gemini(id="gemini-2.5-pro-exp-03-25")
agno_agent = Agent(
name="Serena",
model=model,
# See explanation above on why storage is needed
storage=SqliteStorage(table_name="serena_agent_sessions", db_file=sql_db_path),
description="A fully-featured coding assistant",
tools=[SerenaAgnoToolkit(serena_agent)], # type: ignore
# The tool calls will be shown in the UI anyway since whether to show them is configurable per tool
# To see detailed logs, you should use the serena logger (configure it in the project file path)
show_tool_calls=False,
markdown=True,
system_message=serena_agent.prompt_factory.create_system_prompt(),
telemetry=False,
memory=AgentMemory(),
add_history_to_messages=True,
num_history_responses=100, # you might want to adjust this (expense vs. history awareness)
)
agno_agent = Agent(
name="Serena",
model=model,
# See explanation above on why storage is needed
storage=SqliteStorage(table_name="serena_agent_sessions", db_file=str(sql_db_path)),
description="A fully-featured coding assistant",
tools=[SerenaAgnoToolkit(serena_agent)], # type: ignore
# The tool calls will be shown in the UI anyway since whether to show them is configurable per tool
# To see detailed logs, you should use the serena logger (configure it in the project file path)
show_tool_calls=False,
markdown=True,
system_message=serena_agent.prompt_factory.create_system_prompt(),
telemetry=False,
memory=AgentMemory(),
add_history_to_messages=True,
num_history_responses=100, # you might want to adjust this (expense vs. history awareness)
)
app = Playground(agents=[agno_agent]).get_app()
serve_playground_app("agno_agent:app", reload=False)
app = Playground(agents=[agno_agent]).get_app()
if __name__ == "__main__":
main()
serve_playground_app("agno_agent:app", reload=False)
src/multilspy/language_server.py
+2 -2
View File
@@ -907,7 +907,7 @@ class LanguageServer:
async def request_document_overview(self, relative_file_path: str) -> list[tuple[str, multilspy_types.SymbolKind, int, int]]:
"""
An overview of the given file.
Returns the the list of tuples (name, kind, line, column) of all top-level symbols in the file.
Returns the list of tuples (name, kind, line, column) of all top-level symbols in the file.
"""
_, document_roots = await self.request_document_symbols(relative_file_path)
return [
@@ -1617,7 +1617,7 @@ class SyncLanguageServer:
"""
An overview of the given file.
Returns the the list of tuples (name, kind, line, column) of all top-level symbols in the file.
Returns the list of tuples (name, kind, line, column) of all top-level symbols in the file.
"""
assert self.loop
result = asyncio.run_coroutine_threadsafe(
src/serena/agent.py
+1 -1
View File
@@ -501,7 +501,7 @@ class FindReferencingSymbolsTool(Tool):
:param include_body: whether to include the body of the symbols in the result.
Note that this might lead to a very long output, so you should only use this if you actually need the body
of the referencing symbols for the task at hand. Usually it is a better idea to find
the referencing symbols without the body and then use the find_symbol tool to get the body of
the referencing symbols without the body and then use the find_symbol tool to get the body of
specific symbols if needed.
:param include_kinds: an optional list of integers representing the LSP symbol kinds to include.
If provided, only symbols of the given kinds will be included in the result.